cardiffnlp/tweet_eval
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How to use aXhyra/test_irony_trained_test with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/test_irony_trained_test") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/test_irony_trained_test")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/test_irony_trained_test")This model is a fine-tuned version of distilbert-base-uncased on the tweet_eval dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 358 | 0.6655 | 0.5924 |
| 0.684 | 2.0 | 716 | 0.6889 | 0.6024 |
| 0.5826 | 3.0 | 1074 | 0.7085 | 0.6488 |
| 0.5826 | 4.0 | 1432 | 0.7674 | 0.6680 |